A Software Tool for Assisting Experimentation in Dynamic Environments
In real world, many optimization problems are dynamic, which means that their model elements vary with time. These problems have received increasing attention over time, especially from the viewpoint of metaheuristics methods. In this context, experimentation is a crucial task because of the stocha...
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| Format: | Article |
| Language: | English |
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Wiley
2015-01-01
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| Series: | Applied Computational Intelligence and Soft Computing |
| Online Access: | http://dx.doi.org/10.1155/2015/302172 |
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| author | Pavel Novoa-Hernández Carlos Cruz Corona David A. Pelta |
| author_facet | Pavel Novoa-Hernández Carlos Cruz Corona David A. Pelta |
| author_sort | Pavel Novoa-Hernández |
| collection | DOAJ |
| description | In real world, many optimization problems are dynamic, which means that their
model elements vary with time. These problems have received increasing
attention over time, especially from the viewpoint of metaheuristics methods.
In this context, experimentation is a crucial task because of the
stochastic nature of both algorithms and problems. Currently, there are several
technologies whose methods, problems, and performance measures can be implemented.
However, in most of them, certain features that make the experimentation process easy are
not present. Examples of such features are the statistical analysis of the results and a graphical
user interface (GUI) that allows an easy management of the experimentation process. Bearing in
mind these limitations, in the present work, we present DynOptLab, a software tool for experimental
analysis in dynamic environments. DynOptLab has two main components: (1) an
object-oriented framework to facilitate the implementation of new proposals and
(2) a graphical user interface for the experiment management and the statistical
analysis of the results. With the aim of verifying the benefits of DynOptLab’s main features, a
typical case study on experimentation in dynamic environments was carried out. |
| format | Article |
| id | doaj-art-41dfaea479814e1fb3c1f320d44b0288 |
| institution | Kabale University |
| issn | 1687-9724 1687-9732 |
| language | English |
| publishDate | 2015-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Applied Computational Intelligence and Soft Computing |
| spelling | doaj-art-41dfaea479814e1fb3c1f320d44b02882025-02-03T05:45:43ZengWileyApplied Computational Intelligence and Soft Computing1687-97241687-97322015-01-01201510.1155/2015/302172302172A Software Tool for Assisting Experimentation in Dynamic EnvironmentsPavel Novoa-Hernández0Carlos Cruz Corona1David A. Pelta2Department of Mathematics, University of Holguín, Avenue XX Aniversario S/N, 80100 Holguin, CubaDepartment of Computer Science and Artificial Intelligence, Center for Research in Information and Communication Technologies (CITIC-UGR), University of Granada, Periodista Daniel Saucedo Aranda S/N, 18071 Granada, SpainDepartment of Computer Science and Artificial Intelligence, Center for Research in Information and Communication Technologies (CITIC-UGR), University of Granada, Periodista Daniel Saucedo Aranda S/N, 18071 Granada, SpainIn real world, many optimization problems are dynamic, which means that their model elements vary with time. These problems have received increasing attention over time, especially from the viewpoint of metaheuristics methods. In this context, experimentation is a crucial task because of the stochastic nature of both algorithms and problems. Currently, there are several technologies whose methods, problems, and performance measures can be implemented. However, in most of them, certain features that make the experimentation process easy are not present. Examples of such features are the statistical analysis of the results and a graphical user interface (GUI) that allows an easy management of the experimentation process. Bearing in mind these limitations, in the present work, we present DynOptLab, a software tool for experimental analysis in dynamic environments. DynOptLab has two main components: (1) an object-oriented framework to facilitate the implementation of new proposals and (2) a graphical user interface for the experiment management and the statistical analysis of the results. With the aim of verifying the benefits of DynOptLab’s main features, a typical case study on experimentation in dynamic environments was carried out.http://dx.doi.org/10.1155/2015/302172 |
| spellingShingle | Pavel Novoa-Hernández Carlos Cruz Corona David A. Pelta A Software Tool for Assisting Experimentation in Dynamic Environments Applied Computational Intelligence and Soft Computing |
| title | A Software Tool for Assisting Experimentation in Dynamic Environments |
| title_full | A Software Tool for Assisting Experimentation in Dynamic Environments |
| title_fullStr | A Software Tool for Assisting Experimentation in Dynamic Environments |
| title_full_unstemmed | A Software Tool for Assisting Experimentation in Dynamic Environments |
| title_short | A Software Tool for Assisting Experimentation in Dynamic Environments |
| title_sort | software tool for assisting experimentation in dynamic environments |
| url | http://dx.doi.org/10.1155/2015/302172 |
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